The study, led by postdoctoral fellow Benjamin Decardi-Nelson and Professor Fengqi You, showed that AI can optimise climate and lighting controls in large-scale indoor farms.
Using AI techniques like deep reinforcement learning, researchers found that energy use for growing lettuce in indoor facilities decreased significantly across diverse locations. The findings suggest AI can streamline indoor farming, making it more sustainable and efficient as the global population grows.
By using AI techniques like deep reinforcement learning and computational optimisation, the scientists analysed lettuce cultivated in indoor agriculture facilities within eight US locations – Los Angeles, Chicago, Miami, Seattle, Milwaukee, Phoenix, Fargo, and Ithaca – plus Reykjavík, Iceland and Dubai, United Arab Emirates.
“This is a very similar concept to smart homes,” said Fengqi You professor in energy systems engineering at Cornell. “We want to be comfortable at home while reducing energy use; so do crops. This work focuses on a smart system to make food production optimal, sustainable and lower the carbon footprint. That’s what AI does very well. We can save quite a bit if we use AI to optimise the artificial lighting and other energy systems carefully.”
